The general objective of this proposal is to develop a general protocol to dissect complex gene regulatory networks into elementary modules by integrating stochastic mathematical models with quantitative gene expression experiments in single cells. Gene regulatory networks, especially containing regulatory feedback, exhibit multistability. As genetic regulatory reactions involve small number of molecules, gene expression is stochastic and genetic noise leads to random transitions between the stable states. Therefore, a successful protocol for dissecting complex gene regulatory networks into elementary modules must include both stochastic mathematical methods and gene expression experiments performed on single cells. Both aspects are described in this proposal and are concentrated towards the following three specific aims: (1) Develop a stochastic mathematical model that successfully predicts the connectivity of synthetic genetic networks based on the experimentally obtained multistable dynamics. The expression dynamics of a collection of genetic synthetic networks with arbitrary connectivity will be quantified. Each gene will be monitored by a separate fluorescent protein reporter. As these synthetic networks are well isolated from other genetic modules in the cell, they are ideal calibration tools for mathematical models. (2) Identify the functional role of genetic noise on the bistability of the lactose uptake system of E. coll. The genetic regulation of lactose uptake is, in its simplest form, a positive feedback module leading to two stable states. Preliminary experimental data strongly suggest the presence of these two stable states and demonstrate that genetic noise induces stochastic transitions between the states. The functional role of noise in the context of evolution will be addressed by constructing mathematical models and experiments that explore the fitness of a bistable population in a fluctuating environment. (3) Identify multi-stability in the PTS system of E. coil and explore robustness of different stable states against stochastic fluctuations. The genetic architecture of the PTS system may be modeled as multiple positive feedback loops competing for the same phosphate flux. Mathematical methods will be developed that quantify the multistable behavior of this system illustrated by genetic phase diagrams. The predicted phase diagrams, reflecting the genetic wiring, will be validated by single cell gene expression experiments.